Independent component analysis: An introduction. Issue 2 (4th August 2020)

• Record Type: Journal Article
• Authors: Tharwat, Alaa
• Is Part Of: Applied computing and informatics. Volume 17:Issue 2(2021)
• Page Start: 222
• Page End: 249
• Publication Date: 2020-08-04
• Subjects: Independent component analysis (ICA) -- Blind source separation (BSS) -- Cocktail party problem -- Principal component analysis (PCA); Information science -- Periodicals; Information storage and retrieval systems -- Periodicals; 004
• DOI: 10.1016/j.aci.2018.08.006
• Languages: English
• ISSNs: 2210-8327

Abstract

Abstract : Independent component analysis (ICA) is a widely-used blind source separation technique. ICA has been applied to many applications. ICA is usually utilized as a black box, without understanding its internal details. Therefore, in this paper, the basics of ICA are provided to show how it works to serve as a comprehensive source for researchers who are interested in this field. This paper starts by introducing the definition and underlying principles of ICA. Additionally, different numerical examples in a step-by-step approach are demonstrated to explain the preprocessing steps of ICA and the mixing and unmixing processes in ICA. Moreover, different ICA algorithms, challenges, and applications are presented.